Detection and Verification of the Status of Products Using YOLOv5

Piero Herrera-Toranzo, Juan Castro-Rivera, Willy Ugarte

2023

Abstract

Supermarkets generally do not have an efficient supervisory mechanism for inventory and warehouse management that stockists can use in their day-to-day activities. Our goal is to develop an application based on computer vision models, for the detection, counting and verification of the status of bottled and canned products. Comparisons were made between the different models for the detection of objects through an image, under the verification of parameters, performance and metrics, in order to obtain the best models. Once the YOLOv5 object detection model was chosen, training began with a dataset of own images containing products in good and bad condition in order to identify if they are damaged. Finally, the trained model was coupled to the development of the application. This application allows the user to check which products are in a loaded or taken image, as well as their quantity and status. Additionally, to facilitate the registration tasks of the storekeepers, the application allows keeping a daily record of said products. The mAP@0.5 obtained by our model was 93.09%, while the mAP@0.5:0.95 was 89.04%. Therefore, given the results, this model can perform the task of detecting the status of proposed bottled and canned products.

Paper Citation

in Harvard Style

Herrera-Toranzo P., Castro-Rivera J. and Ugarte W. (2023). Detection and Verification of the Status of Products Using YOLOv5. In Proceedings of the 20th International Conference on Smart Business Technologies - Volume 1: ICSBT; ISBN 978-989-758-667-5, SciTePress, pages 83-93. DOI: 10.5220/0012123500003552

in Bibtex Style

@conference{icsbt23,
author={Piero Herrera-Toranzo and Juan Castro-Rivera and Willy Ugarte},
title={Detection and Verification of the Status of Products Using YOLOv5},
booktitle={Proceedings of the 20th International Conference on Smart Business Technologies - Volume 1: ICSBT},
year={2023},
pages={83-93},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012123500003552},
isbn={978-989-758-667-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Smart Business Technologies - Volume 1: ICSBT
TI - Detection and Verification of the Status of Products Using YOLOv5
SN - 978-989-758-667-5
AU - Herrera-Toranzo P.
AU - Castro-Rivera J.
AU - Ugarte W.
PY - 2023
SP - 83
EP - 93
DO - 10.5220/0012123500003552
PB - SciTePress